title: Quantifying the extent of emphysema: factors associated with radiologists' estimations and quantitative indices of emphysema severity using the ECLIPSE cohort.
abstract: OBJECTIVE
  This study investigated what factors radiologists take into account when estimating emphysema severity and assessed quantitative computed tomography (CT) measurements of low attenuation areas.
  
  
  METHODS
  CT scans and spirometry were obtained on 1519 chronic obstructive pulmonary disease (COPD) subjects, 269 smoker controls, and 184 nonsmoker controls from the Evaluation of COPD Longitudinally to Indentify Surrogate Endpoints (ECLIPSE) study. CT scans were analyzed using the threshold technique (%<-950HU) and a low attenuation cluster analysis. Two radiologists scored emphysema severity (0 to 5 scale), described the predominant type and distribution of emphysema, and the presence of suspected small airways disease.
  
  
  RESULTS
  The percent low attenuation area (%LAA) and visual scores of emphysema severity correlated well (r = 0.77, P < .001). %LAA, low attenuation cluster analysis, and absence of radiologist described gas trapping, distribution, and predominant type of emphysema were predictors of visual scores of emphysema severity (all P < .001). CT scans scored as showing regions of gas trapping had smaller lesions for a similar %LAA than those without (P < .001).
  
  
  CONCLUSIONS
  Visual estimates of emphysema are not only determined by the extent of LAA, but also by lesion size, predominant type, and distribution of emphysema and presence/absence of areas of small airways disease. A computer analysis of low attenuation cluster size helps quantitative algorithms discriminate low attenuation areas from gas trapping, image noise, and emphysema.
authors.affiliation: Department of Radiology, University of British Columbia, Vancouver General Hospital, Canada.
authors.forename: Hester A
authors.initials: HA
authors.lastname: Gietema
authors.forename: Nestor L
authors.initials: NL
authors.lastname: Müller
authors.forename: Paola V Nasute
authors.initials: PV
authors.lastname: Fauerbach
authors.forename: Sanjay
authors.initials: S
authors.lastname: Sharma
authors.forename: Lisa D
authors.initials: LD
authors.lastname: Edwards
authors.forename: Pat G
authors.initials: PG
authors.lastname: Camp
authors.forename: Harvey O
authors.initials: HO
authors.lastname: Coxson
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000704:Analysis of Variance; D015415:Biomarkers; D016022:Case-Control Studies; D016000:Cluster Analysis; D018450:Disease Progression; D005260:Female; D005541:Forced Expiratory Volume; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011656:Pulmonary Emphysema / Q000000981:diagnostic imaging* / Q000503:physiopathology; D011857:Radiographic Image Interpretation, Computer-Assisted; D012044:Regression Analysis; D012720:Severity of Illness Index; D013147:Spirometry; D014057:Tomography, X-Ray Computed
chemical_list: D015415:Biomarkers